Automatic Scraping of dataset options #9
@@ -1,4 +1,5 @@
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import pandas as pd
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import pandas as pd
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import json
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from server.queue.celery_app import celery
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from server.queue.celery_app import celery
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from server.analysis.enrichment import DatasetEnrichment
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from server.analysis.enrichment import DatasetEnrichment
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@@ -37,13 +38,20 @@ def fetch_and_process_dataset(self,
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try:
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try:
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for source_name, source_limit in per_source.items():
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for source_name, source_limit in per_source.items():
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connector = connectors[source_name]()
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connector = connectors[source_name]()
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posts.extend(connector.get_new_posts_by_search(
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raw_posts = connector.get_new_posts_by_search(
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search=search,
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search=search,
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category=category,
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category=category,
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post_limit=source_limit,
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post_limit=source_limit,
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comment_limit=source_limit
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comment_limit=source_limit
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))
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)
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posts.extend(post.to_dict() for post in raw_posts)
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process_dataset.delay(dataset_id, [p.to_dict() for p in posts], topics)
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df = pd.DataFrame(posts)
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processor = DatasetEnrichment(df, topics)
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enriched_df = processor.enrich()
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dataset_manager.save_dataset_content(dataset_id, enriched_df)
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dataset_manager.set_dataset_status(dataset_id, "complete", "NLP Processing Completed Successfully")
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except Exception as e:
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except Exception as e:
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dataset_manager.set_dataset_status(dataset_id, "error", f"An error occurred: {e}")
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dataset_manager.set_dataset_status(dataset_id, "error", f"An error occurred: {e}")
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